Google Cloud’s focus on the enterprise continues apace, with the company announcing its intent to acquire Santa Clara-based cloud storage provider Elastifile.

Elastifile offers cloud-native file storage which promises an enterprise-grade distributed file system, as well as ‘intelligent’ object tiering. While the company had been somewhat under the radar – its most recent funding round of $16 million in 2017 was a little lower than average for cloud storage series Cs – its product set is bang on target for enterprise pain points. The company argues its set of features mean organisations do not need to refactor their apps when migrating to the cloud.

Google plans to integrate Elastifile with Google Cloud Filestore – and writing a blog post confirming the news, Google Cloud CEO Thomas Kurian noted the synergies between the two companies.

“The combination of Elastifile and Google Cloud will support bringing traditional workloads into [Google Cloud Platform] faster and simplify the management and scaling of data and compute intensive workloads,” wrote Kurian. “Furthermore, we believe this combination will empower businesses to build industry-specific, high performance applications that need petabyte-scale file storage more quickly and easily.

“This is critical for industries like media and entertainment, where collaborative artists need shared file storage and the ability to burst compute for image rendering; and life sciences, where genomics processing and machine learning training need speed and consistency; and manufacturing, where jobs like semiconductor design verification can be accelerated by parallelising the simulation models,” added Kurian.

From the Elastifile side, CEO Erwan Menard outlined the rationale behind the move. “As we join the Google Cloud team, we are eager to build further upon our joint success, providing even more value to our customers,” Menard wrote. “Together, we are absolutely convinced that joining Google Cloud will enable us to serve the market with the best file storage service in any cloud, developed in a stimulating environment where our team members will continue to thrive.”

In June, Google Cloud welcomed business intelligence platform Looker into its ranks in what was reported as a $2.6bn (£2.05bn) all-cash transaction. The move was seen as a further indication of Google’s move into multi-cloud, in particular bringing together data from various SaaS applications – another important element for enterprises to consider.

Since Kurian took the top job at Google Cloud plenty has been discussed around the company’s ongoing ambitions, both for enterprise and multi-cloud. During his first public speaking gig in February, Kurian noted his plan to hire more sales staff and focus more aggressively on larger, traditional companies. At Google Next in April, the latter went a step further, with Google announcing its cloud services platform Anthos would accommodate AWS and Microsoft Azure.

Financial terms of the acquisition were not disclosed.

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Keeping your organisation secure in a device- and data-heavy world is tougher than ever. Utilising cloud and artificial intelligence (AI) technologies can lead to various issues – recent coverage has spoken of the problems of hackers ‘hijacking’ AI technology, for instance – but it can also make life easier for security teams.

To get to that harmonious state between human and machine however, a few questions need to be answered along the way. Who does what work? What vectors and bad actors do we need to look out for? Where do we go from here?

Security giant Sophos published a two-part blog last month which aimed to describe the process of fusing artificial intelligence and security and how the company was utilising it.

The company utilises deep learning in particular to recognise malware which nobody else has seen – not only analysing it by its code, but by how it behaves. Sophos analyses more than 2.8 million new malware samples each week, which shows the extent of the challenge and the resources spent combating it.

“When we combine our new data with the hundreds of millions of samples we’ve already collected, our deep learning system can essentially ‘memorise’ the entire observable threat landscape as it stands right now,” the company writes. “Our models help us analyse complex relationships between different features, and we can continually adjust them to target real malware with fewer false positives.”

Erik Farine, regional director for Benelux at Sophos, says that 450,000 new ransomwares or malwares are created per day, of which three quarters could be targeted specifically on one company. “Today we look at behaviour and not at signature anymore,” he tells CloudTech. “There’s no way in keeping track of that without having an AI system that helps us to track that and to make sure that we have a live update on behaviour.”

In May, Oracle published a report which argued this very point. To best protect information systems, across the data, device and application layer, automation and artificial intelligence-based software was needed to give the ‘defence-in-depth’ required to reduce risk, the report explained.

But where does the human side fit in? Plenty has been written across various industries on how AI will fit into organisational structures, with the prevailing consensus being that the human touch would still be needed. When it comes to security, particularly looking at the employee-facing side, the consensus is that the human is the weak link in the chain.

This was also emphasised in the Oracle report. Of the 775 corporate executives polled, the majority said human error was one of the biggest risks to information security. That said, for almost half (47%), the response would be to invest more in people than in technology.

The latter is an opinion with which Farine agrees. Get best practices right and you have got a lot of the job done. “If the AI has to do the work, we’re too late,” he explains. “Make sure that your root ports are closed and make sure that people understand phishing. Those two can rule out lots of intrusions if we manage to do that.”

Another element where Sophos has been looking to utilise deep learning is through its Intercept X offering, focused around endpoint protection. The company announced in May it was adding endpoint detection and response (EDR) to Intercept X for Server. The driving force was a nod to cybercriminals’ evolving habits, frequently blending automation and human hacking skills to carry out attacks on servers.

What’s more, the company is increasingly looking to the cloud, with its Sophos Central unified cloud console, where all security products reside, being claimed as the only vendor doing it today. This is a natural progression, Farine argues; security vendors need to move to ‘as a service’ rather than legacy licensing models.

“If you look at the future, seeing that the market has ramped up in terms of finding people, and finding the know-how, more and more we see that the evolution is towards the cloud, which we are in today,” says Farine. “The next step is it becomes a service. If I look at my region, if you look at the MSP market, that is actually 7% of our business today, and it’s doubling every year.

“It’s evolving very quickly, and from there the step is very small to bring it as a service.”

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The cloud computing ecosystem in China continues to grow; according to a new report the market size rose almost 40% in 2018.

As reported by Xinhua, the China Academy of Information and Communications Technology (CAICT) pegged the Chinese cloud market at 96.28 billian yuan (£11.14bn) last year in its most recent whitepaper, up 39.2% from 2017. The market will almost double in size between now and 2022, CAICT added, forecast to reach 173.1bn yuan.

Regarding the private cloud, the whitepaper put that at 52.5bn yuan for 2018 – up 23.1% year on year – and is expected to reach 117.2bn yuan by 2022.

By 2020, according to a recent missive from the Ministry of Industry and Information Technology, there will be an additional one million enterprises utilising cloud computing in China.

It is one of various proclamations which underscore the country’s potential. According to the most recent analysis from the Asia Cloud Computing Association (ACCA), in April last year, China placed only above Vietnam in a comparison of the primary Asia-Pacific nations. The majority of the problems cited by ACCA relate to China’s size and the long tail of digital transformation, with the country scoring poorly on infrastructure and connectivity.

“The Chinese government continues to devote considerable fiscal resources to the development and improvement of infrastructure, a move that will undoubtedly pay off in the next few years,” the report noted.

When this translates into the roadmap of vendors, Chinese players are starting to make inroads across Asia-Pacific. According to data from Synergy Research in May, the top three players in China are ranked in the top six across APAC as a whole. Alibaba (#2), Tencent (#4) and Sinnet (#6) sit astride Amazon, Microsoft and Google respectively. A large part of this, the research firm noted, is down to China being ‘by far’ the largest country market, growing ‘much faster’ than the rest of the region.

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One of the key inhibitors to progress in DevOps is internal communication – or the lack of it – according to a new survey.

The report, from Trend Micro, polled 1,310 IT decision makers across enterprise and SMB levels and found almost nine in 10 (89%) are lobbying for greater communication between software development and IT security teams.

More than three quarters (77%) said developers, security and operations teams needed to be in closer contact. So where is the breakdown? Only one in three respondents said DevOps was a shared responsibility between software development and IT operations. Enhancing IT security is a greater priority than anything else in building out a DevOps strategy, respondents added.

In total, just under three quarters (74%) said DevOps initiatives had become more important over the past year. One in three (34%) admitted particular silos were making it harder to create DevOps cultures in their organisation.

“History of software development shows that the biggest and best process improvements never happen quickly due to the most valuable variable – people – who have existing behavioural patterns and cultural components,” said Steve Quane, executive vice president of network defence and hybrid cloud security at Trend Micro. “Organisations implementing a DevOps structure are going in a strong direction, but security cannot be forgotten during this transition.”

Writing for this publication earlier this month, Viktor Farcic, principal software delivery strategist at CloudBees, explored the ideal implementation and template. “DevOps is not about creating more silos, nor is it about renaming existing departments as ‘DevOps departments.’ Instead, it’s about people working together to accomplish a common goal: successful release of new features to production,” wrote Farcic.

“When everyone works as a single team focused on a single product, communication improves, the need for administrative overhead decreases, and ownership is established,” Farcic added. “Working together and understanding how one department’s actions affect others create empathy. As a result, productivity and quality increase, and costs and time to market decrease.”

Evidently, there appears to be a way to go before this nirvana is achieved.

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The database market continues to shift to the cloud – and according to Gartner, three quarters of all databases will be deployed or migrated to a cloud platform by 2022.

The finding, which appears in the analyst firm’s latest report, ‘The Future of the DBMS Market is Cloud’, revealed how artificial intelligence was influencing the need for greater data usage. Only 5% of databases will be cloudless by 2022, Gartner added, being considered for ‘repatriation’ to on-premises environments.

Last year, global database management system (DBMS) revenue grew 18.4% to $46 billion (£36.4bn), according to Gartner’s figures. Growth in on-premises systems, the company added, was not down to long term strategy; instead, price increases and forced upgrades are undertaken to mitigate risk.

“According to inquiries with Gartner clients, organisations are developing and deploying new applications in the cloud and moving existing assets at an increasing rate, and we believe this will continue to increase,” said Donald Feinberg, Gartner distinguished research vice president. “We also believe this begins with systems for data management solutions for analytics (DMSA) use cases – such as data warehousing, data lakes, and other use cases where data is used for analytics, artificial intelligence and machine learning.

“Increasingly, operational systems are also moving to the cloud, especially with conversion to the SaaS application model,” Feinberg added.

Of total DMBS revenue growth, cloud database management systems accounted for more than two thirds (68%) of it. Microsoft and Amazon Web Services (AWS), Gartner added, accounted for more than three quarters of that. This gives rise to another trend – that cloud service provider infrastructure is becoming de facto data management platforms.

This is again linked back to multi-cloud, and organisations having to reinforce their strategies due to complex implementations. Gartner recently found that, of respondents who were on the public cloud, more than four in five (81%) were using more than one service provider. “Ultimately what this shows is that the prominence of the CSP infrastructure, its native offerings, and the third-party offerings that run on them is assured,” added Feinberg.

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Digital transformation initiatives require a distinct technological and cultural change – and the element which binds both together is skills.

Yet getting the right skills remain a near-impossibility. The skills gap shows no sign of lessening, with two recent studies proving this point. In December OpsRamp found the vast majority of businesses continued to struggle finding the right talent for cloud environments. Nine out of 10 hiring managers polled agreed the digital skills gap was anywhere between ‘somewhat big’ and ‘huge.’ In the same month, Cloudera found similarly with machine learning (ML); more than half of 200 European IT managers polled said they were reticent at adopting ML technologies because they did not have enough knowledge of the area.

With no real sign of change, IT solutions provider Kainos fears the worst. The company warned last week that skills gaps would continue to widen unless positive action was taken to ensure ‘joined up’ digital skills training initiatives. The company argued current initiatives, particularly in the UK, had scratched the surface but done little more. Earlier this year 12 technology institutes were launched to ‘offer top-quality, higher level technical education [and] help close skills gaps in key STEM areas.’

For Kainos, enterprises, educational establishments and governments need to work more closely to achieve real change, rather than just paying lip service. This is by no means an idle statement either; the company has its own academy, with more than 5,000 users benefiting from it. The process goes from business to education and government, as well as educating parents on potential careers for their children in IT.

Accenture released a report earlier this month focused on expectation versus reality in cloud initiatives. Organisations see the benefits overall, with above 90% satisfaction on average, but only a third of companies polled said they were fully satisfied on cost, speed, and business enablement metrics.

This suggests a gap in itself. “If you listen to what is happening at the CEO table and also what we have seen in our global survey, is that you see there is a clear understanding of the benefits of cloud, the adoption,” Marco Franzen, Accenture Netherlands managing director for technology consulting, tells CloudTech. “If you then look at the results and analyse them, two out of three [companies] think we’re not there yet. They have implemented cloud to some extent but there’s still a new leap, a new platform to reach, above the normal TCO.”

What are the drivers of this gap? Skillsets are certainly one; Franzen notes that smaller-scale companies in particular may be lacking a key skill to ‘make the next move and go all-in on cloud.’ Complexity of change internally was also cited. But the biggest boon, as often tends to be in any cloud study, is security. Two third polled in the Accenture survey said security compliance – particularly handling security in a new cloud-based environment – was of concern.

Is security therefore the biggest stumbling block when it comes to achieving digital skills and digital transformation? It could be argued that it is one area where all the investment in the world won’t bridge the gap. Last month, Oracle released a report which argued better enterprise cybersecurity would need to be remedied through automation rather than a surge in employee training or great security talent being hired. The report, ‘Security in the Age of AI’ (pdf), found the default response for almost half (47%) of respondents was to invest in more people rather than in more technology regarding security.

Tom Gray, CTO at Kainos, notes the importance of automation bridging the gap to some degree with security, but warns against it being the bulwark of any long-term strategy.

“There are an increasing number of areas where the volume of data or the complexity and velocity of the environment makes it impossible for humans, however skilled, to be as effective as an automated solution,” Gray tells CloudTech. “The management of compute and storage infrastructure has become increasingly automated as this infrastructure has evolved from large numbers of modest sized on-premise installations to a small number of large-scale environments whose scale and complexity makes human operation unviable.”

Gray argues organisations need to invest ‘strategically’ in their training to focus on which areas will need further investment and where employees will progress. “It remains to be seen whether automation will create more new jobs than will be lost through automation but, as with today, skills in creating digital technology – as opposed to simply using it – remain in short supply,” he says.

“There is a growing need for skills in identifying opportunities for automation, making best use of the current automation techniques, and understanding and managing the human aspect of automation on both the organisation and broader society,” Gray adds. “Conversely, some of the more repetitive tasks in solution delivery – including some programming, testing, deployment and operations tasks – will inevitably by type for automation.

“It behoves organisations to consider accelerating automation in these areas, rather than trying to build skills that may become unnecessary or, at the very least, prioritise building foundational knowledge and transferable skills to ensure that the individuals and organisation is responsive and resilient to the automation opportunity.”

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It is another case of mind the gap, according to McAfee: while the vast majority of companies are seeing some level of business acceleration through their cloud initiatives, only a fraction are exploiting its full potential.

The security provider has released a special edition of its Cloud and Risk Adoption Report, which polled 1,000 enterprise organisations worldwide alongside collating data from anonymised cloud events across its cloud access security broker (CASB) product.

87% of organisations polled said they do experience some business acceleration from their use of cloud services. More than half (52%) of respondents said they found better security in the cloud than in on-premise IT environments.

Looking at where data resided, almost two thirds (65%) of enterprise data analysed lives in software as a service (SaaS) environments, such as business collaboration tools, with a quarter (25%) in infrastructure as a service (IaaS). The remaining 10% is the big unknown, as shadow IT. Only a third (36%) of those polled said they could enforce data loss prevention in the cloud, with a similar number (33%) saying they could control collaboration settings which determined how data was shared.

The report – as may be expected given how the figures were acquired – explored the impact CASBs made on operations. Not altogether surprisingly, the findings were positive. McAfee argued that organisations were over 35% more likely to launch new products, gain quicker time to market, as well as expanding to new markets, when using a CASB. Despite this, only one in three companies polled were currently using a cloud access security broker.

“This research shines a light on organisations who are leading the charge in cloud adoption, prioritising the security of their data as they roll out new cloud services and winning in the market because of the actions they are taking,” said Rajiv Gupta, senior vice president for cloud security at McAfee. “Organisations often tell us how much faster their business moves when security is addressed in the cloud, and it is exciting for us now to quantify this experience and share our data and recommendations with the rest of the market.”

Read more: Gartner’s latest Magic Quadrant shows the need for cloud access security brokers going forward

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The potential of cloud computing and artificial intelligence (AI) is irresistible. Cloud represents the backbone for any data initiative, and then AI technologies can be used to derive key insights for both greater business intelligence and topline revenue. Yet AI is only as good as the data strategy upon which it sits.

At the AI & Big Data Expo in Amsterdam today, delegates were able to see that the proof of the pudding was in the eating through NetApp's cloud and data fabric initiatives, with Dreamworks Animation cited as a key client who was able to transform its operations.

For the cloud and AI melting pot, however, there are other steps which need to be taken. Patrick Slavenburg, a member of the IoT Council, opened the session with an exploration of how edge computing was taking things further. As Moore's Law finally begins to run out of steam, Slavenburg noted there are up to 70 startups working solely on new microprocessors today. 

Noting how technology history tends to repeat itself, he added today is a heyday for microprocessing architecture for the first time since the 1970s. The key aspect for edge here is being able to perform deep learning at that architectural level, with the algorithms being more lightweight.

Florian Feldhaus, enterprise solutions architect at NetApp, sounded out that data was the key to running AI. According to IDC, by 2020 90% of corporate strategies will explicitly mention data as a critical enterprise asset, and mention analytics as an essential competency. "Wherever you store your data, however you manage it, that's the really important piece to get the benefits of AI," he explained.

The industry continues to insist that it is a multi-cloud, hybrid cloud world today. It is simply no longer a choice between Amazon Web Services (AWS), Microsoft Azure or Google Cloud Platform (GCP), but assessing which workloads fit which cloud. This is also the case in terms of what your company's data scientists are doing, added Feldhaus. Data scientists need to use data wherever they want, he said – use it in every cloud and move the data around to make it available to them.

"You have to fuel data-driven innovation on the world's biggest clouds," said Feldhaus. "There is no way around the cloud." With AI services available in seconds, this was a key point in terms of getting to market. It is also the key metric for data scientists, he added.

NetApp has been gradually moving away from its storage heritage to focus on its 'data fabric' offering – an architecture which offers access to data across multiple endpoints and cloud environments, as well as on-premises. The company announced yesterday an update to its data fabric, with greater integration across Google's cloud as well as support for Kubernetes.

Feldhaus noted the strategy was based on NetApp 'wanting to move to the next step'. Dreamworks was one customer looking at this future, with various big data pipelines allied with the need to process data in a short amount of time.

Ultimately, if organisations want to make the most of the AI opportunity – and time is running out for laggards – then they need their data strategy sorted out. Yes, not everything can be moved to the cloud and some legacy applications need a lot of care and attention, but a more streamlined process is possible. Feldhaus said NetApp's data fabric had four key constituents; discovering the data, activating it, automating, and finally optimising.

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Dropbox has launched a significant redesign, repositioning itself as an enterprise collaboration workspace and moving away from its file storage heritage.

The move will see Dropbox aim to be a one-stop-shop. The relaunched desktop app will enable users to create, access and share content across the Google and Microsoft portfolio, opening Google Docs and Microsoft Office files, offer synchronised search, alongside partnerships with Atlassian, Slack, and Zoom.

The latter partnerships are of particular interest; users will be able to start Slack conversations and share content to Slack channels directly from Dropbox, while also being able to add and join Zoom meetings from Dropbox, as well as again share files. The new features with Atlassian weren’t announced, but Dropbox promises ‘enhanced integrations [to] help teams more effectively manage their projects and content.’

As a blog post from the Dropbox team put it, the primary motivator for the move was to address the ‘work about work’ which slowed many organisations down. “Getting work done requires constant switching between different tools, and coordinating work with your team usually means a mountain of email and meetings,” the company wrote. “It all adds up to a lot of time and energy spent on work that isn’t the actual work itself. But we’ve got a plan, and we’re excited to share how we’re going to help you get a handle on all this ‘work about work.’”

From the company’s perspective, the move makes sense. As regular readers of this publication will be more than aware, the industry – and almost all organisations utilising cloud software – has moved on from simple storage.

Dropbox has made concerted efforts in the past to help customers get more out of their data, rather than the data itself. In October the company upgraded its search engine, Nautilus, to include machine learning capabilities – primarily to help understand and predict users’ needs for documents they search for as and when, rather than being slaves to any one algorithm.

Indeed, it can be argued the company has shifted away from cloud computing as both a marketing message and as an internal business process. Writing for Bloomberg at the time of Dropbox’s IPO filing last March, Shira Ovide noted that the company building out its own infrastructure – a two and a half year project to move away from Amazon Web Services (AWS) – helped make its IPO proposition more viable.

You can read more about the redesign here.

Picture credit: Dropbox

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Late last week, Google announced its intention to acquire business intelligence platform Looker for $2.6 billion (£2.05bn) in an all-cash transaction, with Looker joining Google Cloud upon the acquisition’s close.

For Google Cloud – whose bill is chump change compared to what Salesforce is outlaying for Tableau – Looker represents more options for customers looking to migrate data from legacy technology stacks to BigQuery, Google’s enterprise data warehouse. As Google Cloud chief Thomas Kurian put it, it will help offer customers “a more complete analytics solution from ingesting data to visualising results and integrating data and insights into… daily workflows.” Looker, meanwhile, gets a surrogate while shareholders get a pile of cash. Yet the key to making it all work is multi-cloud.

Google’s primary focus at Next in San Francisco back in April, as this publication noted at the time, was around hybrid cloud, multi-cloud – and in particular open source. The highlight of the keynote was a partnership with seven open source database vendors, including Confluent, MongoDB, and Redis Labs. Looker is compatible across all the major cloud databases, from Amazon Redshift, to Azure SQL, Oracle, and Teradata. CEO Frank Bien confirmed that customers should expect continuing support across all cloud databases.

“[The] announcement also continues our strategic commitment to multi-cloud,” wrote Kurian. “While we deepen the integration of Looker into Google Cloud Platform, customers will continue to benefit from Looker’s multi-cloud functionality and its ability to bring together data from SaaS applications like Salesforce, Marketo, and Zendesk, as well as traditional data sources. This empowers companies to create a cohesive layer built on any cloud database, as well as on other public clouds and in on-premise data centres.

“Looker customers can rest assured that the high-quality support experience that Looker has provided will be bolstered by the resources, expertise, and global presence of our cloud team,” Kurian added. “We will also continue to support best of breed analytics and visualisation tools to provide customers the choice to use a variety of technologies with Google Cloud’s analytics offering.”

Google had long been partners with Looker before the acquisition developed. In July, Looker announced an integration with BigQuery whereby data teams could create machine learning models directly in the latter via the former. The companies shared more than 350 customers, including Buzzfeed, Hearst, and Yahoo!

“The data analytics market is growing incredibly fast as companies look to leverage all of their data to make more informed decisions,” said Frank Gens, senior vice president and chief analyst at IDC. “Google Cloud is one of the leaders in the data warehouse market, and the addition of Looker will further strengthen their ability to serve the needs of enterprise customers while also advancing their commitment to multi-cloud.”

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